The present invention relates to an image processing device for a vehicle, and in particular, relates to an image processing device for a vehicle which recognizes an object in an image by an image recognition processing with a template.
Conventionally, technologies of an image recognition of any object (road signs and the like) in a picked-up image picked by using a template image which has been prepared previously are known (see the following publications, for example). According to the device disclosed in U.S. Patent Application Publication No. 2008/0000289 A1, a so-called template matching processing is executed for the image data of road signs picked up with the template image of the road signs. Herein, the pattern matching is conducted by rotating the template image continuously by a specified angle. In the device of the above-described publication, it is determined that the matching is complete when the matching degree has exceeded a specified level, thereby recognizing the road signs in the image data. According to the device disclosed in Japanese Patent Laid-Open Publication No. 2007-257301, meanwhile, the template matching processing is executed so that the size of the template image can be corrected through extension/reduction, considering the distance to the matching object. Herein, the pattern matching is conducted with this corrected template image. Further, according to the device disclosed in Japanese Patent Laid-Open Publication No. 2008-59319, the template matching processing is executed so that the best template image can be determined by relationships between the matching object and the image features (image coordinates, brightness information, etc.). Moreover, the technical paper (Yasushi Kanazawa et al. “Image Mosaicing by Stratified Matching”, Technical Report D-II of the Institute of Electronics, Information and Communication Engineers, Vol. J86-D-II, No. 6 (2003), pp. 816-824) discloses the method in which the template is transformed by stages in order of translation, analogous transformation, affine transformation, and projective transformation, and then the best transformation is selected by the evaluation index (geometrical AIC), thereby being properly suitable to the rotation, scale change, and projective transformation.
However, the devices disclosed in the above-described first and second publications have some problem in that even though the template image was changed with the rotation or expansion/reduction, this changed template image could not be matched precisely to the object image in case the view of the object image was distorted in the frame image due to positional relationships between the image picking-up means and the object. Thus, the object could not be recognized properly by these devices. In order to solve the above-described problem, it may be considered properly that plural template images which can provide various view angles for each object are prepared and thereby the matching processing is conducted for each of template images. In this case, however, there is another problem in that the processing would be inefficient and the calculation load would be too high. Further, in case the matching processing is executed with relationships of the image features like the device of the above-described third publication, there is further another problem in that the precise matching could not be obtained for the object image with the above-described distorted view. Also, it could be difficult to precisely recognize objects which are different from each other in the kind but have analogous views. Moreover, the method of the above-described last publication has some problem in that since the image transformation is conducted by stages and the selection of the best transformation is conducted by the evaluation index (geometrical AIC), the processing would be inefficient and the calculation load would be too high.